Volunteer Summary

CONSORT Flow Diagram

Overall status

Characteristic

Overall1

Control1

Treatment1

time_point

1st

97

57

40

2nd

65

31

34

1n

Demographic information

Characteristic

N

Overall, N = 971

control, N = 571

treatment, N = 401

p-value2

age

97

39.90 ± 17.68 (19 - 148)

40.28 ± 19.42 (19 - 148)

39.36 ± 15.09 (21 - 70)

0.803

gender

97

0.246

female

69 (71%)

38 (67%)

31 (78%)

male

28 (29%)

19 (33%)

9 (22%)

occupation

97

0.565

civil

3 (3.1%)

2 (3.5%)

1 (2.5%)

clerk

18 (19%)

9 (16%)

9 (22%)

homemaker

8 (8.2%)

3 (5.3%)

5 (12%)

manager

13 (13%)

9 (16%)

4 (10%)

other

10 (10%)

4 (7.0%)

6 (15%)

professional

14 (14%)

11 (19%)

3 (7.5%)

retired

4 (4.1%)

2 (3.5%)

2 (5.0%)

service

4 (4.1%)

2 (3.5%)

2 (5.0%)

student

21 (22%)

14 (25%)

7 (18%)

unemploy

2 (2.1%)

1 (1.8%)

1 (2.5%)

working_status

97

62 (64%)

37 (65%)

25 (62%)

0.808

marital

97

0.834

divorced

3 (3.1%)

1 (1.8%)

2 (5.0%)

married

25 (26%)

15 (26%)

10 (25%)

single

68 (70%)

40 (70%)

28 (70%)

widowed

1 (1.0%)

1 (1.8%)

0 (0%)

marital_r

97

>0.999

married

25 (26%)

15 (26%)

10 (25%)

other

4 (4.1%)

2 (3.5%)

2 (5.0%)

single

68 (70%)

40 (70%)

28 (70%)

education

97

0.009

primary

0 (0%)

0 (0%)

0 (0%)

secondary

11 (11%)

2 (3.5%)

9 (22%)

post-secondary

16 (16%)

12 (21%)

4 (10%)

university

70 (72%)

43 (75%)

27 (68%)

university_edu

97

70 (72%)

43 (75%)

27 (68%)

0.390

family_income

97

0.258

0_10000

11 (11%)

5 (8.8%)

6 (15%)

10001_20000

20 (21%)

8 (14%)

12 (30%)

20001_30000

16 (16%)

11 (19%)

5 (12%)

30001_40000

15 (15%)

10 (18%)

5 (12%)

40000_above

35 (36%)

23 (40%)

12 (30%)

high_income

97

50 (52%)

33 (58%)

17 (42%)

0.135

religion

97

0.490

buddhism

5 (5.2%)

4 (7.0%)

1 (2.5%)

catholic

5 (5.2%)

2 (3.5%)

3 (7.5%)

christianity

36 (37%)

22 (39%)

14 (35%)

nil

49 (51%)

29 (51%)

20 (50%)

other

1 (1.0%)

0 (0%)

1 (2.5%)

taoism

1 (1.0%)

0 (0%)

1 (2.5%)

religion_r

97

>0.999

christianity

41 (42%)

24 (42%)

17 (42%)

nil

49 (51%)

29 (51%)

20 (50%)

other

7 (7.2%)

4 (7.0%)

3 (7.5%)

source

97

0.015

bokss

40 (41%)

19 (33%)

21 (52%)

facebook

15 (15%)

13 (23%)

2 (5.0%)

instagram

6 (6.2%)

6 (11%)

0 (0%)

other

18 (19%)

9 (16%)

9 (22%)

refresh

18 (19%)

10 (18%)

8 (20%)

1Mean ± SD (Range); n (%)

2Two Sample t-test; Pearson's Chi-squared test; Fisher's exact test

Measurement

Characteristic

N

Overall, N = 971

control, N = 571

treatment, N = 401

p-value2

sets

97

19.38 ± 2.22 (15 - 25)

19.04 ± 2.04 (15 - 24)

19.88 ± 2.40 (15 - 25)

0.067

setv

97

11.20 ± 1.65 (8 - 15)

11.04 ± 1.57 (8 - 15)

11.43 ± 1.75 (8 - 15)

0.254

maks

97

44.94 ± 3.81 (36 - 57)

44.58 ± 3.55 (36 - 52)

45.45 ± 4.14 (38 - 57)

0.270

ibs

97

15.56 ± 2.20 (9 - 20)

15.46 ± 2.13 (10 - 20)

15.70 ± 2.31 (9 - 20)

0.593

ers_e

97

12.21 ± 1.44 (8 - 15)

12.16 ± 1.47 (8 - 15)

12.28 ± 1.40 (9 - 15)

0.695

ers_r

97

11.25 ± 1.55 (8 - 15)

11.09 ± 1.49 (8 - 14)

11.47 ± 1.63 (8 - 15)

0.229

pss_pa

97

44.94 ± 4.48 (30 - 54)

44.53 ± 4.28 (30 - 54)

45.52 ± 4.74 (31 - 54)

0.282

pss_ps

97

25.65 ± 7.33 (12 - 42)

26.46 ± 7.51 (13 - 42)

24.50 ± 7.00 (12 - 41)

0.197

pss

97

43.71 ± 11.06 (21 - 72)

44.93 ± 11.16 (22 - 72)

41.98 ± 10.83 (21 - 67)

0.197

rki_responsible

97

21.26 ± 3.93 (13 - 29)

20.95 ± 4.15 (13 - 29)

21.70 ± 3.60 (14 - 28)

0.356

rki_nonlinear

97

13.39 ± 2.69 (6 - 22)

13.19 ± 2.50 (6 - 20)

13.68 ± 2.95 (8 - 22)

0.388

rki_peer

97

20.44 ± 2.12 (16 - 25)

20.49 ± 2.08 (16 - 25)

20.38 ± 2.20 (16 - 25)

0.792

rki_expect

97

4.72 ± 1.07 (2 - 8)

4.58 ± 1.10 (2 - 8)

4.92 ± 1.00 (3 - 7)

0.117

rki

97

59.81 ± 5.80 (45 - 80)

59.21 ± 5.89 (45 - 76)

60.67 ± 5.64 (50 - 80)

0.223

raq_possible

97

15.62 ± 1.80 (12 - 20)

15.68 ± 1.85 (12 - 20)

15.53 ± 1.74 (12 - 20)

0.670

raq_difficulty

97

12.38 ± 1.40 (9 - 15)

12.53 ± 1.39 (9 - 15)

12.18 ± 1.41 (9 - 15)

0.227

raq

97

28.00 ± 2.90 (21 - 35)

28.21 ± 2.96 (21 - 35)

27.70 ± 2.84 (21 - 35)

0.397

who

97

14.77 ± 4.39 (6 - 25)

14.60 ± 4.28 (6 - 25)

15.03 ± 4.59 (6 - 25)

0.639

phq

97

3.58 ± 3.81 (0 - 18)

3.67 ± 3.77 (0 - 17)

3.45 ± 3.92 (0 - 18)

0.785

gad

97

3.16 ± 3.75 (0 - 21)

3.40 ± 4.14 (0 - 21)

2.83 ± 3.11 (0 - 12)

0.457

nb_pcs

97

51.17 ± 7.57 (25 - 63)

51.86 ± 7.23 (25 - 63)

50.20 ± 8.01 (27 - 61)

0.291

nb_mcs

97

50.62 ± 8.60 (22 - 70)

50.01 ± 8.85 (22 - 68)

51.48 ± 8.27 (35 - 70)

0.410

1Mean ± SD (Range)

2Two Sample t-test

Data analysis

Table

Group

Characteristic

Beta

SE1

95% CI1

p-value

sets

(Intercept)

19.0

0.281

18.5, 19.6

group

control

—

—

—

treatment

0.840

0.437

-0.017, 1.70

0.057

time_point

1st

—

—

—

2nd

-0.299

0.387

-1.06, 0.459

0.442

group * time_point

treatment * 2nd

0.174

0.548

-0.900, 1.25

0.752

Pseudo R square

0.045

setv

(Intercept)

11.0

0.221

10.6, 11.5

group

control

—

—

—

treatment

0.390

0.345

-0.285, 1.07

0.260

time_point

1st

—

—

—

2nd

0.209

0.265

-0.310, 0.729

0.432

group * time_point

treatment * 2nd

-0.123

0.373

-0.854, 0.608

0.743

Pseudo R square

0.013

maks

(Intercept)

44.6

0.517

43.6, 45.6

group

control

—

—

—

treatment

0.871

0.804

-0.705, 2.45

0.281

time_point

1st

—

—

—

2nd

-0.156

0.526

-1.19, 0.875

0.768

group * time_point

treatment * 2nd

0.137

0.736

-1.31, 1.58

0.853

Pseudo R square

0.014

ibs

(Intercept)

15.5

0.284

14.9, 16.0

group

control

—

—

—

treatment

0.244

0.442

-0.623, 1.11

0.582

time_point

1st

—

—

—

2nd

0.203

0.312

-0.408, 0.815

0.516

group * time_point

treatment * 2nd

0.324

0.437

-0.534, 1.18

0.462

Pseudo R square

0.017

ers_e

(Intercept)

12.2

0.191

11.8, 12.5

group

control

—

—

—

treatment

0.117

0.297

-0.464, 0.699

0.694

time_point

1st

—

—

—

2nd

-0.512

0.210

-0.924, -0.101

0.017

group * time_point

treatment * 2nd

0.645

0.294

0.069, 1.22

0.032

Pseudo R square

0.031

ers_r

(Intercept)

11.1

0.193

10.7, 11.5

group

control

—

—

—

treatment

0.387

0.301

-0.203, 0.978

0.201

time_point

1st

—

—

—

2nd

-0.086

0.265

-0.605, 0.434

0.747

group * time_point

treatment * 2nd

0.195

0.375

-0.540, 0.931

0.604

Pseudo R square

0.026

pss_pa

(Intercept)

44.5

0.595

43.4, 45.7

group

control

—

—

—

treatment

0.999

0.926

-0.816, 2.81

0.283

time_point

1st

—

—

—

2nd

-1.47

0.797

-3.03, 0.098

0.070

group * time_point

treatment * 2nd

0.589

1.128

-1.62, 2.80

0.603

Pseudo R square

0.032

pss_ps

(Intercept)

26.5

0.967

24.6, 28.4

group

control

—

—

—

treatment

-1.96

1.505

-4.91, 0.994

0.196

time_point

1st

—

—

—

2nd

1.41

1.153

-0.851, 3.67

0.225

group * time_point

treatment * 2nd

-1.42

1.621

-4.60, 1.76

0.384

Pseudo R square

0.032

pss

(Intercept)

44.9

1.437

42.1, 47.7

group

control

—

—

—

treatment

-2.95

2.238

-7.34, 1.43

0.189

time_point

1st

—

—

—

2nd

2.85

1.678

-0.444, 6.13

0.094

group * time_point

treatment * 2nd

-1.96

2.358

-6.58, 2.66

0.408

Pseudo R square

0.035

rki_responsible

(Intercept)

20.9

0.523

19.9, 22.0

group

control

—

—

—

treatment

0.753

0.815

-0.845, 2.35

0.357

time_point

1st

—

—

—

2nd

-0.067

0.632

-1.31, 1.17

0.916

group * time_point

treatment * 2nd

-0.155

0.889

-1.90, 1.59

0.862

Pseudo R square

0.008

rki_nonlinear

(Intercept)

13.2

0.385

12.4, 13.9

group

control

—

—

—

treatment

0.482

0.600

-0.694, 1.66

0.423

time_point

1st

—

—

—

2nd

-0.277

0.461

-1.18, 0.627

0.550

group * time_point

treatment * 2nd

0.461

0.649

-0.811, 1.73

0.480

Pseudo R square

0.014

rki_peer

(Intercept)

20.5

0.295

19.9, 21.1

group

control

—

—

—

treatment

-0.116

0.459

-1.02, 0.783

0.800

time_point

1st

—

—

—

2nd

0.094

0.373

-0.637, 0.824

0.802

group * time_point

treatment * 2nd

0.189

0.525

-0.841, 1.22

0.720

Pseudo R square

0.002

rki_expect

(Intercept)

4.58

0.133

4.32, 4.84

group

control

—

—

—

treatment

0.346

0.208

-0.061, 0.753

0.098

time_point

1st

—

—

—

2nd

0.017

0.197

-0.369, 0.402

0.933

group * time_point

treatment * 2nd

0.177

0.280

-0.372, 0.725

0.530

Pseudo R square

0.047

rki

(Intercept)

59.2

0.785

57.7, 60.7

group

control

—

—

—

treatment

1.46

1.223

-0.932, 3.86

0.233

time_point

1st

—

—

—

2nd

-0.188

0.943

-2.04, 1.66

0.842

group * time_point

treatment * 2nd

0.652

1.327

-1.95, 3.25

0.625

Pseudo R square

0.022

raq_possible

(Intercept)

15.7

0.235

15.2, 16.1

group

control

—

—

—

treatment

-0.159

0.365

-0.875, 0.557

0.664

time_point

1st

—

—

—

2nd

-0.303

0.296

-0.884, 0.277

0.309

group * time_point

treatment * 2nd

0.790

0.418

-0.028, 1.61

0.062

Pseudo R square

0.014

raq_difficulty

(Intercept)

12.5

0.185

12.2, 12.9

group

control

—

—

—

treatment

-0.351

0.288

-0.916, 0.213

0.225

time_point

1st

—

—

—

2nd

-0.107

0.230

-0.557, 0.343

0.643

group * time_point

treatment * 2nd

0.343

0.324

-0.292, 0.977

0.293

Pseudo R square

0.009

raq

(Intercept)

28.2

0.385

27.5, 29.0

group

control

—

—

—

treatment

-0.511

0.600

-1.69, 0.665

0.396

time_point

1st

—

—

—

2nd

-0.357

0.456

-1.25, 0.538

0.437

group * time_point

treatment * 2nd

1.08

0.642

-0.180, 2.33

0.097

Pseudo R square

0.009

who

(Intercept)

14.6

0.577

13.5, 15.7

group

control

—

—

—

treatment

0.429

0.899

-1.33, 2.19

0.634

time_point

1st

—

—

—

2nd

-0.134

0.616

-1.34, 1.07

0.828

group * time_point

treatment * 2nd

0.675

0.863

-1.02, 2.37

0.437

Pseudo R square

0.009

phq

(Intercept)

3.67

0.483

2.72, 4.61

group

control

—

—

—

treatment

-0.217

0.751

-1.69, 1.26

0.774

time_point

1st

—

—

—

2nd

0.128

0.397

-0.651, 0.906

0.749

group * time_point

treatment * 2nd

-0.068

0.553

-1.15, 1.02

0.902

Pseudo R square

0.001

gad

(Intercept)

3.40

0.487

2.45, 4.36

group

control

—

—

—

treatment

-0.579

0.758

-2.06, 0.907

0.447

time_point

1st

—

—

—

2nd

0.114

0.462

-0.793, 1.02

0.807

group * time_point

treatment * 2nd

-0.033

0.646

-1.30, 1.23

0.959

Pseudo R square

0.006

nb_pcs

(Intercept)

51.9

0.963

50.0, 53.7

group

control

—

—

—

treatment

-1.66

1.500

-4.60, 1.28

0.272

time_point

1st

—

—

—

2nd

-0.982

0.930

-2.80, 0.841

0.294

group * time_point

treatment * 2nd

2.05

1.299

-0.496, 4.60

0.119

Pseudo R square

0.008

nb_mcs

(Intercept)

50.0

1.104

47.8, 52.2

group

control

—

—

—

treatment

1.47

1.719

-1.90, 4.84

0.394

time_point

1st

—

—

—

2nd

0.027

1.286

-2.49, 2.55

0.983

group * time_point

treatment * 2nd

-0.010

1.807

-3.55, 3.53

0.996

Pseudo R square

0.008

1SE = Standard Error, CI = Confidence Interval

Text

sets

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict sets with group and time_point (formula: sets ~ 1 + group + time_point + group * time_point). The model included login_id as random effect (formula: ~1 | login_id). The model’s total explanatory power is substantial (conditional R2 = 0.43) and the part related to the fixed effects alone (marginal R2) is of 0.04. The model’s intercept, corresponding to group = control and time_point = 1st, is at 19.04 (95% CI [18.48, 19.59], t(156) = 67.81, p < .001). Within this model:

  • The effect of group [treatment] is statistically non-significant and positive (beta = 0.84, 95% CI [-0.02, 1.70], t(156) = 1.92, p = 0.055; Std. beta = 0.39, 95% CI [-7.85e-03, 0.79])
  • The effect of time point [2nd] is statistically non-significant and negative (beta = -0.30, 95% CI [-1.06, 0.46], t(156) = -0.77, p = 0.440; Std. beta = -0.14, 95% CI [-0.49, 0.21])
  • The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and positive (beta = 0.17, 95% CI [-0.90, 1.25], t(156) = 0.32, p = 0.751; Std. beta = 0.08, 95% CI [-0.42, 0.58])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

setv

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict setv with group and time_point (formula: setv ~ 1 + group + time_point + group * time_point). The model included login_id as random effect (formula: ~1 | login_id). The model’s total explanatory power is substantial (conditional R2 = 0.57) and the part related to the fixed effects alone (marginal R2) is of 0.01. The model’s intercept, corresponding to group = control and time_point = 1st, is at 11.04 (95% CI [10.60, 11.47], t(156) = 49.87, p < .001). Within this model:

  • The effect of group [treatment] is statistically non-significant and positive (beta = 0.39, 95% CI [-0.29, 1.07], t(156) = 1.13, p = 0.258; Std. beta = 0.23, 95% CI [-0.17, 0.63])
  • The effect of time point [2nd] is statistically non-significant and positive (beta = 0.21, 95% CI [-0.31, 0.73], t(156) = 0.79, p = 0.430; Std. beta = 0.12, 95% CI [-0.18, 0.43])
  • The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and negative (beta = -0.12, 95% CI [-0.85, 0.61], t(156) = -0.33, p = 0.742; Std. beta = -0.07, 95% CI [-0.51, 0.36])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

maks

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict maks with group and time_point (formula: maks ~ 1 + group + time_point + group * time_point). The model included login_id as random effect (formula: ~1 | login_id). The model’s total explanatory power is substantial (conditional R2 = 0.70) and the part related to the fixed effects alone (marginal R2) is of 0.01. The model’s intercept, corresponding to group = control and time_point = 1st, is at 44.58 (95% CI [43.57, 45.59], t(156) = 86.31, p < .001). Within this model:

  • The effect of group [treatment] is statistically non-significant and positive (beta = 0.87, 95% CI [-0.71, 2.45], t(156) = 1.08, p = 0.279; Std. beta = 0.22, 95% CI [-0.18, 0.63])
  • The effect of time point [2nd] is statistically non-significant and negative (beta = -0.16, 95% CI [-1.19, 0.88], t(156) = -0.30, p = 0.767; Std. beta = -0.04, 95% CI [-0.31, 0.22])
  • The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and positive (beta = 0.14, 95% CI [-1.31, 1.58], t(156) = 0.19, p = 0.852; Std. beta = 0.04, 95% CI [-0.34, 0.41])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

ibs

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict ibs with group and time_point (formula: ibs ~ 1 + group + time_point + group * time_point). The model included login_id as random effect (formula: ~1 | login_id). The model’s total explanatory power is substantial (conditional R2 = 0.65) and the part related to the fixed effects alone (marginal R2) is of 0.02. The model’s intercept, corresponding to group = control and time_point = 1st, is at 15.46 (95% CI [14.90, 16.01], t(156) = 54.44, p < .001). Within this model:

  • The effect of group [treatment] is statistically non-significant and positive (beta = 0.24, 95% CI [-0.62, 1.11], t(156) = 0.55, p = 0.581; Std. beta = 0.11, 95% CI [-0.29, 0.52])
  • The effect of time point [2nd] is statistically non-significant and positive (beta = 0.20, 95% CI [-0.41, 0.81], t(156) = 0.65, p = 0.514; Std. beta = 0.09, 95% CI [-0.19, 0.38])
  • The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and positive (beta = 0.32, 95% CI [-0.53, 1.18], t(156) = 0.74, p = 0.459; Std. beta = 0.15, 95% CI [-0.25, 0.55])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

ers_e

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict ers_e with group and time_point (formula: ers_e ~ 1 + group + time_point + group * time_point). The model included login_id as random effect (formula: ~1 | login_id). The model’s total explanatory power is substantial (conditional R2 = 0.65) and the part related to the fixed effects alone (marginal R2) is of 0.03. The model’s intercept, corresponding to group = control and time_point = 1st, is at 12.16 (95% CI [11.78, 12.53], t(156) = 63.82, p < .001). Within this model:

  • The effect of group [treatment] is statistically non-significant and positive (beta = 0.12, 95% CI [-0.46, 0.70], t(156) = 0.39, p = 0.693; Std. beta = 0.08, 95% CI [-0.32, 0.48])
  • The effect of time point [2nd] is statistically significant and negative (beta = -0.51, 95% CI [-0.92, -0.10], t(156) = -2.44, p = 0.015; Std. beta = -0.35, 95% CI [-0.64, -0.07])
  • The interaction effect of time point [2nd] on group [treatment] is statistically significant and positive (beta = 0.65, 95% CI [0.07, 1.22], t(156) = 2.19, p = 0.028; Std. beta = 0.45, 95% CI [0.05, 0.85])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

ers_r

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict ers_r with group and time_point (formula: ers_r ~ 1 + group + time_point + group * time_point). The model included login_id as random effect (formula: ~1 | login_id). The model’s total explanatory power is substantial (conditional R2 = 0.43) and the part related to the fixed effects alone (marginal R2) is of 0.03. The model’s intercept, corresponding to group = control and time_point = 1st, is at 11.09 (95% CI [10.71, 11.47], t(156) = 57.30, p < .001). Within this model:

  • The effect of group [treatment] is statistically non-significant and positive (beta = 0.39, 95% CI [-0.20, 0.98], t(156) = 1.29, p = 0.199; Std. beta = 0.26, 95% CI [-0.14, 0.67])
  • The effect of time point [2nd] is statistically non-significant and negative (beta = -0.09, 95% CI [-0.61, 0.43], t(156) = -0.32, p = 0.746; Std. beta = -0.06, 95% CI [-0.41, 0.30])
  • The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and positive (beta = 0.20, 95% CI [-0.54, 0.93], t(156) = 0.52, p = 0.603; Std. beta = 0.13, 95% CI [-0.37, 0.64])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

pss_pa

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict pss_pa with group and time_point (formula: pss_pa ~ 1 + group + time_point + group * time_point). The model included login_id as random effect (formula: ~1 | login_id). The model’s total explanatory power is substantial (conditional R2 = 0.46) and the part related to the fixed effects alone (marginal R2) is of 0.03. The model’s intercept, corresponding to group = control and time_point = 1st, is at 44.53 (95% CI [43.36, 45.69], t(156) = 74.87, p < .001). Within this model:

  • The effect of group [treatment] is statistically non-significant and positive (beta = 1.00, 95% CI [-0.82, 2.81], t(156) = 1.08, p = 0.281; Std. beta = 0.22, 95% CI [-0.18, 0.62])
  • The effect of time point [2nd] is statistically non-significant and negative (beta = -1.47, 95% CI [-3.03, 0.10], t(156) = -1.84, p = 0.066; Std. beta = -0.32, 95% CI [-0.66, 0.02])
  • The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and positive (beta = 0.59, 95% CI [-1.62, 2.80], t(156) = 0.52, p = 0.602; Std. beta = 0.13, 95% CI [-0.36, 0.61])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

pss_ps

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict pss_ps with group and time_point (formula: pss_ps ~ 1 + group + time_point + group * time_point). The model included login_id as random effect (formula: ~1 | login_id). The model’s total explanatory power is substantial (conditional R2 = 0.59) and the part related to the fixed effects alone (marginal R2) is of 0.03. The model’s intercept, corresponding to group = control and time_point = 1st, is at 26.46 (95% CI [24.56, 28.35], t(156) = 27.37, p < .001). Within this model:

  • The effect of group [treatment] is statistically non-significant and negative (beta = -1.96, 95% CI [-4.91, 0.99], t(156) = -1.30, p = 0.194; Std. beta = -0.26, 95% CI [-0.66, 0.13])
  • The effect of time point [2nd] is statistically non-significant and positive (beta = 1.41, 95% CI [-0.85, 3.67], t(156) = 1.22, p = 0.222; Std. beta = 0.19, 95% CI [-0.12, 0.50])
  • The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and negative (beta = -1.42, 95% CI [-4.60, 1.76], t(156) = -0.88, p = 0.381; Std. beta = -0.19, 95% CI [-0.62, 0.24])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

pss

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict pss with group and time_point (formula: pss ~ 1 + group + time_point + group * time_point). The model included login_id as random effect (formula: ~1 | login_id). The model’s total explanatory power is substantial (conditional R2 = 0.61) and the part related to the fixed effects alone (marginal R2) is of 0.03. The model’s intercept, corresponding to group = control and time_point = 1st, is at 44.93 (95% CI [42.11, 47.75], t(156) = 31.26, p < .001). Within this model:

  • The effect of group [treatment] is statistically non-significant and negative (beta = -2.95, 95% CI [-7.34, 1.43], t(156) = -1.32, p = 0.187; Std. beta = -0.27, 95% CI [-0.66, 0.13])
  • The effect of time point [2nd] is statistically non-significant and positive (beta = 2.85, 95% CI [-0.44, 6.13], t(156) = 1.70, p = 0.090; Std. beta = 0.26, 95% CI [-0.04, 0.56])
  • The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and negative (beta = -1.96, 95% CI [-6.58, 2.66], t(156) = -0.83, p = 0.405; Std. beta = -0.18, 95% CI [-0.60, 0.24])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

rki_responsible

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict rki_responsible with group and time_point (formula: rki_responsible ~ 1 + group + time_point + group * time_point). The model included login_id as random effect (formula: ~1 | login_id). The model’s total explanatory power is substantial (conditional R2 = 0.56) and the part related to the fixed effects alone (marginal R2) is of 7.61e-03. The model’s intercept, corresponding to group = control and time_point = 1st, is at 20.95 (95% CI [19.92, 21.97], t(156) = 40.03, p < .001). Within this model:

  • The effect of group [treatment] is statistically non-significant and positive (beta = 0.75, 95% CI [-0.84, 2.35], t(156) = 0.92, p = 0.356; Std. beta = 0.19, 95% CI [-0.22, 0.60])
  • The effect of time point [2nd] is statistically non-significant and negative (beta = -0.07, 95% CI [-1.31, 1.17], t(156) = -0.11, p = 0.916; Std. beta = -0.02, 95% CI [-0.33, 0.30])
  • The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and negative (beta = -0.16, 95% CI [-1.90, 1.59], t(156) = -0.17, p = 0.861; Std. beta = -0.04, 95% CI [-0.49, 0.41])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

rki_nonlinear

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict rki_nonlinear with group and time_point (formula: rki_nonlinear ~ 1 + group + time_point + group * time_point). The model included login_id as random effect (formula: ~1 | login_id). The model’s total explanatory power is substantial (conditional R2 = 0.57) and the part related to the fixed effects alone (marginal R2) is of 0.01. The model’s intercept, corresponding to group = control and time_point = 1st, is at 13.19 (95% CI [12.44, 13.95], t(156) = 34.24, p < .001). Within this model:

  • The effect of group [treatment] is statistically non-significant and positive (beta = 0.48, 95% CI [-0.69, 1.66], t(156) = 0.80, p = 0.422; Std. beta = 0.17, 95% CI [-0.24, 0.57])
  • The effect of time point [2nd] is statistically non-significant and negative (beta = -0.28, 95% CI [-1.18, 0.63], t(156) = -0.60, p = 0.548; Std. beta = -0.10, 95% CI [-0.41, 0.22])
  • The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and positive (beta = 0.46, 95% CI [-0.81, 1.73], t(156) = 0.71, p = 0.477; Std. beta = 0.16, 95% CI [-0.28, 0.60])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

rki_peer

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict rki_peer with group and time_point (formula: rki_peer ~ 1 + group + time_point + group * time_point). The model included login_id as random effect (formula: ~1 | login_id). The model’s total explanatory power is substantial (conditional R2 = 0.51) and the part related to the fixed effects alone (marginal R2) is of 2.08e-03. The model’s intercept, corresponding to group = control and time_point = 1st, is at 20.49 (95% CI [19.91, 21.07], t(156) = 69.57, p < .001). Within this model:

  • The effect of group [treatment] is statistically non-significant and negative (beta = -0.12, 95% CI [-1.02, 0.78], t(156) = -0.25, p = 0.800; Std. beta = -0.05, 95% CI [-0.46, 0.35])
  • The effect of time point [2nd] is statistically non-significant and positive (beta = 0.09, 95% CI [-0.64, 0.82], t(156) = 0.25, p = 0.801; Std. beta = 0.04, 95% CI [-0.29, 0.37])
  • The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and positive (beta = 0.19, 95% CI [-0.84, 1.22], t(156) = 0.36, p = 0.719; Std. beta = 0.09, 95% CI [-0.38, 0.55])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

rki_expect

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict rki_expect with group and time_point (formula: rki_expect ~ 1 + group + time_point + group * time_point). The model included login_id as random effect (formula: ~1 | login_id). The model’s total explanatory power is substantial (conditional R2 = 0.33) and the part related to the fixed effects alone (marginal R2) is of 0.05. The model’s intercept, corresponding to group = control and time_point = 1st, is at 4.58 (95% CI [4.32, 4.84], t(156) = 34.34, p < .001). Within this model:

  • The effect of group [treatment] is statistically non-significant and positive (beta = 0.35, 95% CI [-0.06, 0.75], t(156) = 1.67, p = 0.096; Std. beta = 0.34, 95% CI [-0.06, 0.74])
  • The effect of time point [2nd] is statistically non-significant and positive (beta = 0.02, 95% CI [-0.37, 0.40], t(156) = 0.08, p = 0.933; Std. beta = 0.02, 95% CI [-0.36, 0.39])
  • The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and positive (beta = 0.18, 95% CI [-0.37, 0.73], t(156) = 0.63, p = 0.528; Std. beta = 0.17, 95% CI [-0.37, 0.71])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

rki

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict rki with group and time_point (formula: rki ~ 1 + group + time_point + group * time_point). The model included login_id as random effect (formula: ~1 | login_id). The model’s total explanatory power is substantial (conditional R2 = 0.57) and the part related to the fixed effects alone (marginal R2) is of 0.02. The model’s intercept, corresponding to group = control and time_point = 1st, is at 59.21 (95% CI [57.67, 60.75], t(156) = 75.41, p < .001). Within this model:

  • The effect of group [treatment] is statistically non-significant and positive (beta = 1.46, 95% CI [-0.93, 3.86], t(156) = 1.20, p = 0.231; Std. beta = 0.25, 95% CI [-0.16, 0.66])
  • The effect of time point [2nd] is statistically non-significant and negative (beta = -0.19, 95% CI [-2.04, 1.66], t(156) = -0.20, p = 0.842; Std. beta = -0.03, 95% CI [-0.35, 0.28])
  • The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and positive (beta = 0.65, 95% CI [-1.95, 3.25], t(156) = 0.49, p = 0.623; Std. beta = 0.11, 95% CI [-0.33, 0.56])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

raq_possible

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict raq_possible with group and time_point (formula: raq_possible ~ 1 + group + time_point + group * time_point). The model included login_id as random effect (formula: ~1 | login_id). The model’s total explanatory power is substantial (conditional R2 = 0.52) and the part related to the fixed effects alone (marginal R2) is of 0.01. The model’s intercept, corresponding to group = control and time_point = 1st, is at 15.68 (95% CI [15.22, 16.14], t(156) = 66.86, p < .001). Within this model:

  • The effect of group [treatment] is statistically non-significant and negative (beta = -0.16, 95% CI [-0.88, 0.56], t(156) = -0.44, p = 0.663; Std. beta = -0.09, 95% CI [-0.49, 0.31])
  • The effect of time point [2nd] is statistically non-significant and negative (beta = -0.30, 95% CI [-0.88, 0.28], t(156) = -1.02, p = 0.306; Std. beta = -0.17, 95% CI [-0.50, 0.16])
  • The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and positive (beta = 0.79, 95% CI [-0.03, 1.61], t(156) = 1.89, p = 0.059; Std. beta = 0.44, 95% CI [-0.02, 0.91])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

raq_difficulty

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict raq_difficulty with group and time_point (formula: raq_difficulty ~ 1 + group + time_point + group * time_point). The model included login_id as random effect (formula: ~1 | login_id). The model’s total explanatory power is substantial (conditional R2 = 0.53) and the part related to the fixed effects alone (marginal R2) is of 9.29e-03. The model’s intercept, corresponding to group = control and time_point = 1st, is at 12.53 (95% CI [12.16, 12.89], t(156) = 67.69, p < .001). Within this model:

  • The effect of group [treatment] is statistically non-significant and negative (beta = -0.35, 95% CI [-0.92, 0.21], t(156) = -1.22, p = 0.223; Std. beta = -0.25, 95% CI [-0.65, 0.15])
  • The effect of time point [2nd] is statistically non-significant and negative (beta = -0.11, 95% CI [-0.56, 0.34], t(156) = -0.46, p = 0.642; Std. beta = -0.08, 95% CI [-0.40, 0.25])
  • The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and positive (beta = 0.34, 95% CI [-0.29, 0.98], t(156) = 1.06, p = 0.290; Std. beta = 0.24, 95% CI [-0.21, 0.70])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

raq

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict raq with group and time_point (formula: raq ~ 1 + group + time_point + group * time_point). The model included login_id as random effect (formula: ~1 | login_id). The model’s total explanatory power is substantial (conditional R2 = 0.58) and the part related to the fixed effects alone (marginal R2) is of 8.90e-03. The model’s intercept, corresponding to group = control and time_point = 1st, is at 28.21 (95% CI [27.46, 28.97], t(156) = 73.27, p < .001). Within this model:

  • The effect of group [treatment] is statistically non-significant and negative (beta = -0.51, 95% CI [-1.69, 0.66], t(156) = -0.85, p = 0.395; Std. beta = -0.18, 95% CI [-0.58, 0.23])
  • The effect of time point [2nd] is statistically non-significant and negative (beta = -0.36, 95% CI [-1.25, 0.54], t(156) = -0.78, p = 0.434; Std. beta = -0.12, 95% CI [-0.43, 0.18])
  • The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and positive (beta = 1.08, 95% CI [-0.18, 2.33], t(156) = 1.68, p = 0.093; Std. beta = 0.37, 95% CI [-0.06, 0.80])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

who

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict who with group and time_point (formula: who ~ 1 + group + time_point + group * time_point). The model included login_id as random effect (formula: ~1 | login_id). The model’s total explanatory power is substantial (conditional R2 = 0.67) and the part related to the fixed effects alone (marginal R2) is of 8.70e-03. The model’s intercept, corresponding to group = control and time_point = 1st, is at 14.60 (95% CI [13.47, 15.73], t(156) = 25.29, p < .001). Within this model:

  • The effect of group [treatment] is statistically non-significant and positive (beta = 0.43, 95% CI [-1.33, 2.19], t(156) = 0.48, p = 0.634; Std. beta = 0.10, 95% CI [-0.31, 0.51])
  • The effect of time point [2nd] is statistically non-significant and negative (beta = -0.13, 95% CI [-1.34, 1.07], t(156) = -0.22, p = 0.828; Std. beta = -0.03, 95% CI [-0.31, 0.25])
  • The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and positive (beta = 0.67, 95% CI [-1.02, 2.37], t(156) = 0.78, p = 0.434; Std. beta = 0.16, 95% CI [-0.24, 0.55])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

phq

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict phq with group and time_point (formula: phq ~ 1 + group + time_point + group * time_point). The model included login_id as random effect (formula: ~1 | login_id). The model’s total explanatory power is substantial (conditional R2 = 0.81) and the part related to the fixed effects alone (marginal R2) is of 1.22e-03. The model’s intercept, corresponding to group = control and time_point = 1st, is at 3.67 (95% CI [2.72, 4.61], t(156) = 7.60, p < .001). Within this model:

  • The effect of group [treatment] is statistically non-significant and negative (beta = -0.22, 95% CI [-1.69, 1.26], t(156) = -0.29, p = 0.773; Std. beta = -0.06, 95% CI [-0.47, 0.35])
  • The effect of time point [2nd] is statistically non-significant and positive (beta = 0.13, 95% CI [-0.65, 0.91], t(156) = 0.32, p = 0.748; Std. beta = 0.04, 95% CI [-0.18, 0.25])
  • The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and negative (beta = -0.07, 95% CI [-1.15, 1.02], t(156) = -0.12, p = 0.902; Std. beta = -0.02, 95% CI [-0.32, 0.28])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

gad

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict gad with group and time_point (formula: gad ~ 1 + group + time_point + group * time_point). The model included login_id as random effect (formula: ~1 | login_id). The model’s total explanatory power is substantial (conditional R2 = 0.74) and the part related to the fixed effects alone (marginal R2) is of 6.39e-03. The model’s intercept, corresponding to group = control and time_point = 1st, is at 3.40 (95% CI [2.45, 4.36], t(156) = 6.99, p < .001). Within this model:

  • The effect of group [treatment] is statistically non-significant and negative (beta = -0.58, 95% CI [-2.06, 0.91], t(156) = -0.76, p = 0.445; Std. beta = -0.16, 95% CI [-0.59, 0.26])
  • The effect of time point [2nd] is statistically non-significant and positive (beta = 0.11, 95% CI [-0.79, 1.02], t(156) = 0.25, p = 0.806; Std. beta = 0.03, 95% CI [-0.22, 0.29])
  • The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and negative (beta = -0.03, 95% CI [-1.30, 1.23], t(156) = -0.05, p = 0.959; Std. beta = -9.47e-03, 95% CI [-0.37, 0.35])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

nb_pcs

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict nb_pcs with group and time_point (formula: nb_pcs ~ 1 + group + time_point + group * time_point). The model included login_id as random effect (formula: ~1 | login_id). The model’s total explanatory power is substantial (conditional R2 = 0.73) and the part related to the fixed effects alone (marginal R2) is of 7.85e-03. The model’s intercept, corresponding to group = control and time_point = 1st, is at 51.86 (95% CI [49.97, 53.74], t(156) = 53.85, p < .001). Within this model:

  • The effect of group [treatment] is statistically non-significant and negative (beta = -1.66, 95% CI [-4.60, 1.28], t(156) = -1.10, p = 0.269; Std. beta = -0.23, 95% CI [-0.63, 0.17])
  • The effect of time point [2nd] is statistically non-significant and negative (beta = -0.98, 95% CI [-2.80, 0.84], t(156) = -1.06, p = 0.291; Std. beta = -0.13, 95% CI [-0.38, 0.11])
  • The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and positive (beta = 2.05, 95% CI [-0.50, 4.60], t(156) = 1.58, p = 0.115; Std. beta = 0.28, 95% CI [-0.07, 0.63])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

nb_mcs

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict nb_mcs with group and time_point (formula: nb_mcs ~ 1 + group + time_point + group * time_point). The model included login_id as random effect (formula: ~1 | login_id). The model’s total explanatory power is substantial (conditional R2 = 0.60) and the part related to the fixed effects alone (marginal R2) is of 7.70e-03. The model’s intercept, corresponding to group = control and time_point = 1st, is at 50.01 (95% CI [47.85, 52.18], t(156) = 45.31, p < .001). Within this model:

  • The effect of group [treatment] is statistically non-significant and positive (beta = 1.47, 95% CI [-1.90, 4.84], t(156) = 0.86, p = 0.392; Std. beta = 0.18, 95% CI [-0.23, 0.59])
  • The effect of time point [2nd] is statistically non-significant and positive (beta = 0.03, 95% CI [-2.49, 2.55], t(156) = 0.02, p = 0.983; Std. beta = 3.30e-03, 95% CI [-0.30, 0.31])
  • The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and negative (beta = -9.95e-03, 95% CI [-3.55, 3.53], t(156) = -5.51e-03, p = 0.996; Std. beta = -1.21e-03, 95% CI [-0.43, 0.43])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

Likelihood ratio tests

outcome

model

npar

AIC

BIC

logLik

deviance

Chisq

Df

p

sets

null

3

699.516

708.779

-346.758

693.516

sets

random

6

699.541

718.067

-343.771

687.541

5.975

3

0.113

setv

null

3

604.947

614.210

-299.473

598.947

setv

random

6

608.833

627.359

-298.417

596.833

2.114

3

0.549

maks

null

3

860.921

870.184

-427.460

854.921

maks

random

6

865.372

883.898

-426.686

853.372

1.548

3

0.671

ibs

null

3

678.506

687.769

-336.253

672.506

ibs

random

6

680.104

698.630

-334.052

668.104

4.402

3

0.221

ers_e

null

3

552.731

561.994

-273.366

546.731

ers_e

random

6

551.065

569.591

-269.533

539.065

7.666

3

0.053

ers_r

null

3

575.868

585.130

-284.934

569.868

ers_r

random

6

578.487

597.013

-283.244

566.487

3.380

3

0.337

pss_pa

null

3

940.630

949.893

-467.315

934.630

pss_pa

random

6

940.325

958.851

-464.163

928.325

6.305

3

0.098

pss_ps

null

3

1,084.490

1,093.753

-539.245

1,078.490

pss_ps

random

6

1,085.966

1,104.491

-536.983

1,073.966

4.525

3

0.210

pss

null

3

1,212.215

1,221.478

-603.107

1,206.215

pss

random

6

1,212.251

1,230.776

-600.125

1,200.251

5.964

3

0.113

rki_responsible

null

3

883.481

892.743

-438.740

877.481

rki_responsible

random

6

888.498

907.023

-438.249

876.498

0.983

3

0.805

rki_nonlinear

null

3

784.338

793.601

-389.169

778.338

rki_nonlinear

random

6

788.388

806.914

-388.194

776.388

1.949

3

0.583

rki_peer

null

3

701.708

710.970

-347.854

695.708

rki_peer

random

6

707.044

725.570

-347.522

695.044

0.663

3

0.882

rki_expect

null

3

464.700

473.962

-229.350

458.700

rki_expect

random

6

463.889

482.414

-225.944

451.889

6.811

3

0.078

rki

null

3

1,016.078

1,025.341

-505.039

1,010.078

rki

random

6

1,019.367

1,037.893

-503.683

1,007.367

2.712

3

0.438

raq_possible

null

3

631.148

640.411

-312.574

625.148

raq_possible

random

6

633.112

651.637

-310.556

621.112

4.036

3

0.258

raq_difficulty

null

3

550.528

559.791

-272.264

544.528

raq_difficulty

random

6

554.525

573.050

-271.262

542.525

2.003

3

0.572

raq

null

3

784.306

793.569

-389.153

778.306

raq

random

6

787.068

805.594

-387.534

775.068

3.237

3

0.356

who

null

3

902.299

911.562

-448.150

896.299

who

random

6

906.717

925.243

-447.358

894.717

1.582

3

0.663

phq

null

3

812.265

821.528

-403.133

806.265

phq

random

6

818.035

836.561

-403.018

806.035

0.230

3

0.973

gad

null

3

832.719

841.982

-413.359

826.719

gad

random

6

837.975

856.500

-412.987

825.975

0.744

3

0.863

nb_pcs

null

3

1,057.974

1,067.237

-525.987

1,051.974

nb_pcs

random

6

1,061.019

1,079.544

-524.509

1,049.019

2.956

3

0.399

nb_mcs

null

3

1,121.338

1,130.600

-557.669

1,115.338

nb_mcs

random

6

1,126.455

1,144.981

-557.228

1,114.455

0.882

3

0.830

Post hoc analysis text

Table

outcome

time

control

treatment

between

n

estimate

within es

n

estimate

within es

p

es

sets

1st

57

19.04 ± 2.12

40

19.87 ± 2.12

0.057

-0.513

sets

2nd

31

18.74 ± 2.05

0.182

34

19.75 ± 2.10

0.076

0.051

-0.619

setv

1st

57

11.04 ± 1.67

40

11.42 ± 1.67

0.260

-0.354

setv

2nd

31

11.24 ± 1.55

-0.190

34

11.51 ± 1.63

-0.079

0.500

-0.243

maks

1st

57

44.58 ± 3.90

40

45.45 ± 3.90

0.281

-0.406

maks

2nd

31

44.42 ± 3.45

0.073

34

45.43 ± 3.76

0.009

0.261

-0.470

ibs

1st

57

15.46 ± 2.14

40

15.70 ± 2.14

0.582

-0.190

ibs

2nd

31

15.66 ± 1.94

-0.159

34

16.23 ± 2.08

-0.411

0.256

-0.443

ers_e

1st

57

12.16 ± 1.44

40

12.27 ± 1.44

0.694

-0.136

ers_e

2nd

31

11.65 ± 1.30

0.595

34

12.41 ± 1.39

-0.154

0.024

-0.885

ers_r

1st

57

11.09 ± 1.46

40

11.47 ± 1.46

0.201

-0.345

ers_r

2nd

31

11.00 ± 1.41

0.076

34

11.58 ± 1.44

-0.098

0.102

-0.520

pss_pa

1st

57

44.53 ± 4.49

40

45.53 ± 4.49

0.283

-0.297

pss_pa

2nd

31

43.06 ± 4.31

0.436

34

44.65 ± 4.43

0.261

0.145

-0.472

pss_ps

1st

57

26.46 ± 7.30

40

24.50 ± 7.30

0.196

0.409

pss_ps

2nd

31

27.86 ± 6.76

-0.295

34

24.49 ± 7.12

0.003

0.052

0.707

pss

1st

57

44.93 ± 10.85

40

41.98 ± 10.85

0.189

0.426

pss

2nd

31

47.78 ± 9.98

-0.410

34

42.86 ± 10.57

-0.127

0.056

0.709

rki_responsible

1st

57

20.95 ± 3.95

40

21.70 ± 3.95

0.357

-0.287

rki_responsible

2nd

31

20.88 ± 3.67

0.026

34

21.48 ± 3.86

0.085

0.524

-0.228

rki_nonlinear

1st

57

13.19 ± 2.91

40

13.68 ± 2.91

0.423

-0.252

rki_nonlinear

2nd

31

12.92 ± 2.70

0.145

34

13.86 ± 2.84

-0.096

0.172

-0.493

rki_peer

1st

57

20.49 ± 2.22

40

20.37 ± 2.22

0.800

0.075

rki_peer

2nd

31

20.59 ± 2.10

-0.060

34

20.66 ± 2.18

-0.182

0.891

-0.047

rki_expect

1st

57

4.58 ± 1.01

40

4.92 ± 1.01

0.098

-0.410

rki_expect

2nd

31

4.60 ± 0.99

-0.020

34

5.12 ± 1.00

-0.229

0.036

-0.619

rki

1st

57

59.21 ± 5.93

40

60.67 ± 5.93

0.233

-0.374

rki

2nd

31

59.02 ± 5.50

0.048

34

61.14 ± 5.79

-0.118

0.133

-0.541

raq_possible

1st

57

15.68 ± 1.77

40

15.52 ± 1.77

0.664

0.129

raq_possible

2nd

31

15.38 ± 1.67

0.245

34

16.01 ± 1.74

-0.394

0.137

-0.510

raq_difficulty

1st

57

12.53 ± 1.40

40

12.18 ± 1.40

0.225

0.367

raq_difficulty

2nd

31

12.42 ± 1.31

0.112

34

12.41 ± 1.37

-0.247

0.980

0.009

raq

1st

57

28.21 ± 2.91

40

27.70 ± 2.91

0.396

0.270

raq

2nd

31

27.85 ± 2.69

0.189

34

28.42 ± 2.84

-0.381

0.409

-0.300

who

1st

57

14.60 ± 4.36

40

15.02 ± 4.36

0.634

-0.170

who

2nd

31

14.46 ± 3.90

0.053

34

15.57 ± 4.21

-0.214

0.275

-0.437

phq

1st

57

3.67 ± 3.64

40

3.45 ± 3.64

0.774

0.135

phq

2nd

31

3.79 ± 3.06

-0.080

34

3.51 ± 3.46

-0.037

0.725

0.178

gad

1st

57

3.40 ± 3.67

40

2.82 ± 3.67

0.447

0.308

gad

2nd

31

3.52 ± 3.19

-0.061

34

2.91 ± 3.52

-0.043

0.464

0.326

nb_pcs

1st

57

51.86 ± 7.27

40

50.20 ± 7.27

0.272

0.438

nb_pcs

2nd

31

50.88 ± 6.34

0.260

34

51.27 ± 6.98

-0.283

0.812

-0.104

nb_mcs

1st

57

50.01 ± 8.33

40

51.48 ± 8.33

0.394

-0.277

nb_mcs

2nd

31

50.04 ± 7.66

-0.005

34

51.50 ± 8.12

-0.003

0.457

-0.275

Between group

sets

1st

t(140.40) = 1.92, p = 0.057, Cohen d = -0.51, 95% CI (-0.02 to 1.70)

2st

t(156.07) = 1.97, p = 0.051, Cohen d = -0.62, 95% CI (-0.00 to 2.03)

setv

1st

t(127.40) = 1.13, p = 0.260, Cohen d = -0.35, 95% CI (-0.29 to 1.07)

2st

t(151.77) = 0.68, p = 0.500, Cohen d = -0.24, 95% CI (-0.51 to 1.05)

maks

1st

t(116.80) = 1.08, p = 0.281, Cohen d = -0.41, 95% CI (-0.72 to 2.46)

2st

t(143.80) = 1.13, p = 0.261, Cohen d = -0.47, 95% CI (-0.76 to 2.77)

ibs

1st

t(121.18) = 0.55, p = 0.582, Cohen d = -0.19, 95% CI (-0.63 to 1.12)

2st

t(147.81) = 1.14, p = 0.256, Cohen d = -0.44, 95% CI (-0.42 to 1.55)

ers_e

1st

t(121.31) = 0.39, p = 0.694, Cohen d = -0.14, 95% CI (-0.47 to 0.70)

2st

t(147.91) = 2.28, p = 0.024, Cohen d = -0.88, 95% CI (0.10 to 1.42)

ers_r

1st

t(139.81) = 1.29, p = 0.201, Cohen d = -0.35, 95% CI (-0.21 to 0.98)

2st

t(155.95) = 1.64, p = 0.102, Cohen d = -0.52, 95% CI (-0.12 to 1.28)

pss_pa

1st

t(137.60) = 1.08, p = 0.283, Cohen d = -0.30, 95% CI (-0.83 to 2.83)

2st

t(155.45) = 1.46, p = 0.145, Cohen d = -0.47, 95% CI (-0.55 to 3.73)

pss_ps

1st

t(126.98) = -1.30, p = 0.196, Cohen d = 0.41, 95% CI (-4.93 to 1.02)

2st

t(151.56) = -1.96, p = 0.052, Cohen d = 0.71, 95% CI (-6.78 to 0.03)

pss

1st

t(125.35) = -1.32, p = 0.189, Cohen d = 0.43, 95% CI (-7.38 to 1.48)

2st

t(150.66) = -1.93, p = 0.056, Cohen d = 0.71, 95% CI (-9.96 to 0.12)

rki_responsible

1st

t(128.00) = 0.92, p = 0.357, Cohen d = -0.29, 95% CI (-0.86 to 2.37)

2st

t(152.07) = 0.64, p = 0.524, Cohen d = -0.23, 95% CI (-1.25 to 2.44)

rki_nonlinear

1st

t(127.30) = 0.80, p = 0.423, Cohen d = -0.25, 95% CI (-0.71 to 1.67)

2st

t(151.72) = 1.37, p = 0.172, Cohen d = -0.49, 95% CI (-0.41 to 2.30)

rki_peer

1st

t(131.99) = -0.25, p = 0.800, Cohen d = 0.07, 95% CI (-1.02 to 0.79)

2st

t(153.76) = 0.14, p = 0.891, Cohen d = -0.05, 95% CI (-0.98 to 1.12)

rki_expect

1st

t(147.87) = 1.67, p = 0.098, Cohen d = -0.41, 95% CI (-0.06 to 0.76)

2st

t(157.21) = 2.11, p = 0.036, Cohen d = -0.62, 95% CI (0.03 to 1.01)

rki

1st

t(127.56) = 1.20, p = 0.233, Cohen d = -0.37, 95% CI (-0.95 to 3.88)

2st

t(151.85) = 1.51, p = 0.133, Cohen d = -0.54, 95% CI (-0.65 to 4.88)

raq_possible

1st

t(131.84) = -0.44, p = 0.664, Cohen d = 0.13, 95% CI (-0.88 to 0.56)

2st

t(153.70) = 1.49, p = 0.137, Cohen d = -0.51, 95% CI (-0.20 to 1.47)

raq_difficulty

1st

t(130.32) = -1.22, p = 0.225, Cohen d = 0.37, 95% CI (-0.92 to 0.22)

2st

t(153.11) = -0.03, p = 0.980, Cohen d = 0.01, 95% CI (-0.67 to 0.65)

raq

1st

t(126.50) = -0.85, p = 0.396, Cohen d = 0.27, 95% CI (-1.70 to 0.68)

2st

t(151.30) = 0.83, p = 0.409, Cohen d = -0.30, 95% CI (-0.79 to 1.92)

who

1st

t(119.42) = 0.48, p = 0.634, Cohen d = -0.17, 95% CI (-1.35 to 2.21)

2st

t(146.34) = 1.10, p = 0.275, Cohen d = -0.44, 95% CI (-0.89 to 3.09)

phq

1st

t(108.30) = -0.29, p = 0.774, Cohen d = 0.14, 95% CI (-1.71 to 1.27)

2st

t(131.66) = -0.35, p = 0.725, Cohen d = 0.18, 95% CI (-1.88 to 1.31)

gad

1st

t(113.49) = -0.76, p = 0.447, Cohen d = 0.31, 95% CI (-2.08 to 0.92)

2st

t(139.86) = -0.74, p = 0.464, Cohen d = 0.33, 95% CI (-2.26 to 1.03)

nb_pcs

1st

t(114.22) = -1.10, p = 0.272, Cohen d = 0.44, 95% CI (-4.63 to 1.31)

2st

t(140.81) = 0.24, p = 0.812, Cohen d = -0.10, 95% CI (-2.87 to 3.66)

nb_mcs

1st

t(125.19) = 0.86, p = 0.394, Cohen d = -0.28, 95% CI (-1.93 to 4.87)

2st

t(150.56) = 0.75, p = 0.457, Cohen d = -0.27, 95% CI (-2.41 to 5.33)

Within treatment group

sets

1st vs 2st

t(70.13) = -0.32, p = 0.749, Cohen d = 0.08, 95% CI (-0.90 to 0.65)

setv

1st vs 2st

t(67.87) = 0.33, p = 0.743, Cohen d = -0.08, 95% CI (-0.44 to 0.61)

maks

1st vs 2st

t(66.23) = -0.04, p = 0.971, Cohen d = 0.01, 95% CI (-1.05 to 1.01)

ibs

1st vs 2st

t(66.89) = 1.72, p = 0.090, Cohen d = -0.41, 95% CI (-0.09 to 1.14)

ers_e

1st vs 2st

t(66.91) = 0.64, p = 0.522, Cohen d = -0.15, 95% CI (-0.28 to 0.54)

ers_r

1st vs 2st

t(70.02) = 0.41, p = 0.681, Cohen d = -0.10, 95% CI (-0.42 to 0.64)

pss_pa

1st vs 2st

t(69.61) = -1.10, p = 0.277, Cohen d = 0.26, 95% CI (-2.47 to 0.72)

pss_ps

1st vs 2st

t(67.80) = -0.01, p = 0.991, Cohen d = 0.00, 95% CI (-2.29 to 2.27)

pss

1st vs 2st

t(67.54) = 0.53, p = 0.597, Cohen d = -0.13, 95% CI (-2.43 to 4.19)

rki_responsible

1st vs 2st

t(67.96) = -0.35, p = 0.724, Cohen d = 0.08, 95% CI (-1.47 to 1.03)

rki_nonlinear

1st vs 2st

t(67.85) = 0.40, p = 0.688, Cohen d = -0.10, 95% CI (-0.73 to 1.10)

rki_peer

1st vs 2st

t(68.62) = 0.76, p = 0.449, Cohen d = -0.18, 95% CI (-0.46 to 1.02)

rki_expect

1st vs 2st

t(71.76) = 0.97, p = 0.336, Cohen d = -0.23, 95% CI (-0.20 to 0.59)

rki

1st vs 2st

t(67.89) = 0.50, p = 0.622, Cohen d = -0.12, 95% CI (-1.40 to 2.33)

raq_possible

1st vs 2st

t(68.59) = 1.65, p = 0.103, Cohen d = -0.39, 95% CI (-0.10 to 1.08)

raq_difficulty

1st vs 2st

t(68.34) = 1.03, p = 0.305, Cohen d = -0.25, 95% CI (-0.22 to 0.69)

raq

1st vs 2st

t(67.72) = 1.60, p = 0.115, Cohen d = -0.38, 95% CI (-0.18 to 1.62)

who

1st vs 2st

t(66.62) = 0.89, p = 0.375, Cohen d = -0.21, 95% CI (-0.67 to 1.75)

phq

1st vs 2st

t(64.97) = 0.15, p = 0.878, Cohen d = -0.04, 95% CI (-0.71 to 0.83)

gad

1st vs 2st

t(65.73) = 0.18, p = 0.859, Cohen d = -0.04, 95% CI (-0.82 to 0.98)

nb_pcs

1st vs 2st

t(65.84) = 1.18, p = 0.244, Cohen d = -0.28, 95% CI (-0.74 to 2.88)

nb_mcs

1st vs 2st

t(67.51) = 0.01, p = 0.989, Cohen d = -0.00, 95% CI (-2.52 to 2.55)

Within control group

sets

1st vs 2st

t(83.21) = -0.77, p = 0.444, Cohen d = 0.18, 95% CI (-1.07 to 0.47)

setv

1st vs 2st

t(77.20) = 0.79, p = 0.434, Cohen d = -0.19, 95% CI (-0.32 to 0.74)

maks

1st vs 2st

t(72.59) = -0.30, p = 0.769, Cohen d = 0.07, 95% CI (-1.21 to 0.90)

ibs

1st vs 2st

t(74.48) = 0.65, p = 0.518, Cohen d = -0.16, 95% CI (-0.42 to 0.83)

ers_e

1st vs 2st

t(74.54) = -2.43, p = 0.017, Cohen d = 0.59, 95% CI (-0.93 to -0.09)

ers_r

1st vs 2st

t(82.92) = -0.32, p = 0.748, Cohen d = 0.08, 95% CI (-0.62 to 0.44)

pss_pa

1st vs 2st

t(81.85) = -1.83, p = 0.071, Cohen d = 0.44, 95% CI (-3.06 to 0.13)

pss_ps

1st vs 2st

t(77.02) = 1.22, p = 0.227, Cohen d = -0.29, 95% CI (-0.90 to 3.71)

pss

1st vs 2st

t(76.30) = 1.69, p = 0.095, Cohen d = -0.41, 95% CI (-0.51 to 6.20)

rki_responsible

1st vs 2st

t(77.47) = -0.11, p = 0.916, Cohen d = 0.03, 95% CI (-1.33 to 1.20)

rki_nonlinear

1st vs 2st

t(77.16) = -0.60, p = 0.552, Cohen d = 0.14, 95% CI (-1.20 to 0.65)

rki_peer

1st vs 2st

t(79.25) = 0.25, p = 0.803, Cohen d = -0.06, 95% CI (-0.65 to 0.84)

rki_expect

1st vs 2st

t(87.18) = 0.08, p = 0.933, Cohen d = -0.02, 95% CI (-0.38 to 0.41)

rki

1st vs 2st

t(77.27) = -0.20, p = 0.843, Cohen d = 0.05, 95% CI (-2.07 to 1.70)

raq_possible

1st vs 2st

t(79.18) = -1.02, p = 0.311, Cohen d = 0.25, 95% CI (-0.90 to 0.29)

raq_difficulty

1st vs 2st

t(78.50) = -0.46, p = 0.645, Cohen d = 0.11, 95% CI (-0.57 to 0.35)

raq

1st vs 2st

t(76.80) = -0.78, p = 0.439, Cohen d = 0.19, 95% CI (-1.27 to 0.56)

who

1st vs 2st

t(73.72) = -0.22, p = 0.829, Cohen d = 0.05, 95% CI (-1.37 to 1.10)

phq

1st vs 2st

t(68.91) = 0.32, p = 0.749, Cohen d = -0.08, 95% CI (-0.67 to 0.92)

gad

1st vs 2st

t(71.16) = 0.24, p = 0.807, Cohen d = -0.06, 95% CI (-0.81 to 1.04)

nb_pcs

1st vs 2st

t(71.48) = -1.05, p = 0.296, Cohen d = 0.26, 95% CI (-2.84 to 0.88)

nb_mcs

1st vs 2st

t(76.23) = 0.02, p = 0.983, Cohen d = -0.01, 95% CI (-2.54 to 2.60)

Plot